Scopus İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395

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In-silico Identification of Papillary Thyroid Carcinoma Molecular Mechanisms
(IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA, 2019) Ersoz, Nur Sebnem; Guzel, Yasin; Bakir-Gungor, Burcu
Representing approximately 70% to 80% of thyroid cancers, papillary thyroid cancer (PTC) is the most common type of thyroid cancers. PTC is seen in all age groups, but it is seen more frequently in women than in men. Detection of biomarker proteins of papillary thyroid cancinoma plays an important role in the diagnosis of the disease. In this study, we aim to find target genes and pathways that are associated with papillar thyroid carcinoma, by integrating different bioinformatics methods. For this purpose, usingin-silico methodologies, candidate genes and pathways that could explain disease development mechanisms are identified. Throughout this study, firstly we identified differentially expressed genes as the amount of their protein product differ between patient and healthy groups. Secondly, by using active subnetworks search algorithms, topologic analyses and functional enrichment tests, candidate proteins,which could be thought as PTC biomarkers, and affected pathways are identified.
Ensemble Churn Prediction for Internet Service Provider with Machine Learning Techniques
(IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA, 2020) Goy, Gokhan; Kolukisa, Burak; Bahcevan, Cenk; Gungor, Vehbi Cagri
With the developing technology in every fields, a competitive marketing environment has been arised In this competitive environment analyzing customer behavior has become vital In particular, the ability to easily change any service provider has become vet) , critical for the company to continue its existence At the same time, the amount of financial resources spent on retaining instituters much less than to obtain new clients. In this context, the traditional methods of examining vast amount of data obtained today for establishing decision support systems have lost their validities In this study. we used a dataset which is provided by TurkNet serving as an internet service provider in Turkey. Various preprocessing steps has performed on this dataset and then classification algorithms ran. Afterwards results have obtained and compared. The results of these experiments analyzed in terms of the area under the curve value In this context the aunt successful classifier algorithm has been determined as the Random Trees algorithm with a value of 0.936.
Computer-Aided Classification of Breast Cancer Histopathological Images
(IEEE345 E 47TH ST, NEW YORK, NY 10017 USA, 2017) Aksebzeci, Bekir Hakan; Kayaalti, Omer
Nowadays, one of the most common types of cancer is breast cancer. The early and accurate diagnosis of breast cancer has great importance in the treatment of the disease. In the diagnosis of breast cancer, histopathological analysis of cell and tissue specimens taken by biopsy is considered as the gold standard. Histopathological analysis is a tedious process that is highly dependent on the knowledge and experience of the pathologists. In this study; it is aimed to develop a computer-aided system that can reduce the workload of pathologists and help them in their diagnosis. An image set containing benign and malignant tumor images of breast cancer has been studied. To perform texture analysis on tumor images; first order statistics, Gabor and gray-level co-occurrence matrix (GLCM) feature extraction methods have been applied. Then, various classifiers were applied to the obtained feature matrices and their performances were compared. The highest classification accuracy was achieved 82.06% by Random Forests classifier with feature combination of Gabor and GLCM methods. The results presented here show that computer-assisted diagnosis of breast cancer is a promising field.
Real-Time Robotic Car Control Using Brainwaves and Head Movement
(IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA, 2018) Ozturk, Nedime; Yilmaz, Bulent; Onver, Ahmet Yasin
Emotiv Epoc Headset is a portable and low-cost device. In this study, Emotiv Epoc headset was used in order to obtain real-time gyro and EEG signals. The aim of this study was to control a robotic car in real-time by using head movement and opening and closing of the eyes. The maximum and minimum amplitude of the gyro signal, and the ratios of the beta waves of O1 and O2 channel to alpha waves of the same channels were used as threshold values. These threshold values were used to determine the direction of the robotic car. Because of its low-cost and easy implementation, Arduino Uno was used to manage the robotic car. This study has shown that brain waves and head movements can control a device in real time. This system has the potential to be used in neurofeedback and brain-computer interface applications.
Yenilenebilir Enerji İçin Ödeme İstekliliği Ve Bu İstekliliği Etkileyen Faktörlerin Analiz Edilmesi
(TUBİTAK, 2018) Doğan, Eyüp
Bu projede, Türkiye?de ikamet eden hanehalkının yenilenebilir enerji için ödeme istekliliği (YÖİS) ve bu istekliliği etkileyen faktörler analiz edilecektir. İlgili literatür kapsamında, gelişmiş ve gelişmekte olan birçok ülke için YÖİS ve bu istekliliğe etki eden faktörler incelenmesine rağmen, daha önce bu alanda Türkiye üzerine bir çalışma yapılmamıştır. Bu projenin amacı, Türkiye?deki vatandaşların YÖİS ve bu istekliliği etkileyen değişkenleri inceleyerek literatürdeki bu boşluğu doldurmaktır. Ayrıca, Sundt ve Rehdanz (2015) ?ın meta-analiz çalışması, ilgili literatürdeki çoğu makalenin yaş, eğitim seviyesi, gelir düzeyi ve çevresel duyarlılık gibi faktörlerin olası etkisini analiz etmesine rağmen sadece bir kaç makalenin hanehalkı sayısını ekonometrik modele dahil ettiğini göstermiştir. Bu proje, coğunlukla kullanılan demografik faktörlerin yanısıra hanehalkı sayısınında YÖİS?i etkileyip etkilemediğini araştıracaktır. Bu projeyi gerçekleştirebilmek için koşullu değer yöntemiyle hazırlanan toplam 2 bölüm ve 26 sorudan oluşan bir anket kullanılacaktır. Yüzyüze görüşme yöntemiyle Türkiye?nin 12 farklı İBBS bölgesinden toplam 2,500 kişiyle yüzyüze görüşme yöntemiyle doldurulacak anketlerden elde edilecek bilgiler sayesinde, Türkiye?de ikamet eden hanehalkının ortalama YÖİS miktarı ve hangi faktörlerin bu istekliliği anlamlı yada anlamsız etkilediği çeşitli yöntemler kullanılarak analiz edilecektir. Türkiye, Avrupa Birliğine aday bir ülke, G-20 ekonomilerinden birisi ve NATO?ya dahil bir ülke olmasının yanısıra, Dünya ve Avrupa enerji piyasasında da önemli bir konuma sahiptir. Ayrıca, yenilenebilir enerji alanında kısa ve orta vadede yapılması hedeflenen yatırımlarda göz önüne alındığında, Türkiye bu literatür içerisinde araştırılması gereken ülkelerin arasındadır. Bununla birlikte, son zamanlarda küresel ısınma, gaz emisyonu ve çevresel kirlilik gibi faktörler global bir sorun haline gelmiştir. Yenilenebilir enerjinin kullanımı daha temiz bir çevre için önemli bir unsurdur. Türkiye enerjide dışa bağımlı bir ülkedir. Ayrıca, Türkiye'nin elektrik enerjisinin %48'inin doğal gazdan üretiliyor olmasının yarattığı kırılganlığın son dönem Rusya krizi ile görülmüş olması sonrasında enerji karmasında çeşitlendirme çok daha hassasiyet kazanmıştır. Yenilenebilir enerjinin artırılması bağımlılığı azaltacak önemli bir araçtır. Hanehalklarının katılımı, hedeflenen yenilenebilir enerji projelerinin hayata geçirilmesini kolaylaştıracaktır. Bu proje dört ana hedefe ulaşmak üzerine odaklanmıştır: i) Türkiye?de ikamet eden hanehalklarının yenilenebilir kaynalardan üretilen elektrik enerjisi almak için ödemeye razı oldukları ortalama miktarı bulmak, ii) YÖİS?i etkileyebilecek yaş, cinsiyet, gelir düzeyi, egitim seviyesi, çevreye olan duyarlılık ve hanehalkı sayısı gibi faktörleri analiz etmek, iii) yenilenebilir enerji yatırımlarının hanehalkları tarafından desteklenmesine olanak sağlayacak bir politikanın Türkiye?de uygulanabilirliğini ortaya koymak, iv) bu proje çıktılarını uluslararası indekslerce taranan bir dergide yayınlatmak.
Detection of Variation Instances on Colonoscopy Videos using Structural Similarity Index
(IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA, 2018) Kacmaz, Rukiye Nur; Yilmaz, Bulent
The aim of this study is to reduce the number of images extracted from the videos recorded by the specialists during the colonoscopy process for further examination, thereby enabling the specialist to deal with fewer images. Since the images obtained from the videos are very similar, the main assumption of this study is that the whole video can be represented by fewer images. The approach used in this study is the structural similarity index. Totally, images were obtained from 4 different videos coming from healthy, ulcerative colitis, Crohn's, and polyp patients. The noisy images in these videos were eliminated manually. When the structural similarity index between two consecutive clear images was less than 0.83, the second image was selected and shown to the specialist for his/her examination. By this way, the frames carrying significantly new information from the videos were defined as the variation instances. The tests on healthy or diseased colon videos showed that only 5-10% of the clear images provide significantly new information.
Identification of Shared Pathways Among Immune Related Diseases Utilizing Active Subnetworks
(IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA, 2020) Eryilmaz, Mahmut Kaan; Kuzudisli, Cihan; Gungor, Burcu Bakir
Different, but related diseases often contain shared symptoms indicating the presence of possible overlaps in underlying pathogenic mechanisms. The identification of the shared pathways and related factors across these diseases helps to better understand the causes of these diseases, to prevent and treat these diseases. In this study, using immune-related diseases, we proposed a new method on how to compare the development mechanisms of related diseases based on biological pathways. Following the developments in genomic technologies, the genotyping gets cheaper and easier, and hence genome-wide association studies (GWAS) emerged. By this means, via studying big-sized case-control groups for a specific disease, potential genetic variations, single nucleotide polymorphisms (SNPs) could he identified. With the help of these studies, in which around a million of SNPs are scanned, the variations and genes that could have a role in specific disease development could be detected. In this study, via using available GWAS datasets and human protein-protein interaction network, and via detecting active subnetworks and affected pathways, seven immune related diseases are analyzed. Via investigating the similarities among the identified pathways for related diseases, we aim to define the underlying pathogenic mechanisms, and hence to contribute to the elucidation of disease development mechanisms and to the drug repositioning studies.
A New Method to Identify Affected Pathway Subnetworks and Clusters in Colon Cancer
(IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA, 2019) Goy, Gokhan; Yazici, Miray Unlu; Bakir-Gungor, Buren
Nowadays new technological developments that play an important role in the production of big data have brought about the interpretation, sharing and storage of data related to complex diseases. Combining multi-omic data in different molecular levels is potentially important for understanding the biological origin of complex diseases. One of these complex diseases is cancer of different types, which has one of the highest causes of death worldwide. The integration of multiple omic data in the framework of a comprehensive analysis and identification of relevant pathways contribute to the development of therapeutic approaches related to disease. In this study, RNA and methylation data (genes and p values) of colon adenocarcinoma were obtained from TCGA data portal and combined with Fisher's method. While protein subnetworks affected by the disease were identified by using subnetwork algorithm, pathways related to the disease and genes associated with these pathways were determined by functional enrichment analysis. Using gene-pathway relationship matrix, kappa scores of pathways were determined by similarity calculation. In this way, the pathways were clustered according to the hierarchically optimal number, as a result, the most important pathway clusters and related genes that are effective in disease formation identified.
In-Silico Methods to Identify Common MicroRNAs and Pathways of Neuromuscular Diseases
(IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA, 2019) Yazici, Miray Unlu; Menges, Evrim Aksu; Ulum, Yeliz Z. Akkaya; Hayta, Burcu Balci; Bakir-Gungor, Burcu
Neuromuscular disorders (NMD) are a heterogeneous group of diseases characterized by the loss of function of the peripheral nerves and muscles. However, there are no effective and widespread therapeutic approaches to prevent or delay the progression of these disease types. microRNAs (miRNAs) which cause significant changes in gene expression by binding to target messenger RNAs (mRNAs), are known to have an effect on disease mechanisms. In this study, by integrating different bioinformatics methods, we aim to find miRNAs, target genes and pathways related to a group of neuromuscular diseases. For this purpose, we determined 17 miRNAs that show significant expression changes between patient and healthy groups; predicted target genes of these miRNAs; and identified affected pathways using subnetwork discovery, functional enrichment based algorithms. In our study, we integrated different in-silico approaches that proceed in top-down manner or bottom-up manner. The identified candidate miRNAs, genes and pathways, which could help to explain neuromuscular disease development mechanisms, are now under investigation in wet-lab.
Bor Zengini Amorf Malzemeler
(TUBİTAK, 2020) Durandurdu, Murat
Bu TÜBİTAK 1001 projesi kapsamında, bor zengini farklı amorf malzemeler [B1-xSix, B1-xCx, B1-_x000D_ xOx, ve B1-xLix (0, 5 ≥ � ≥ 0,05)] ab initio moleküler dinamik tekniği kullanılarak sıvı hallerin hızlıca_x000D_ soğutulması sonucu modellenmiş ve bu malzemelerin atomik yapıları, elektronik yapıları ve_x000D_ mekanik özellikleri ayrıntı olarak araştırılmıştır. Bunlara ek olarak, bu malzemelerin bazı_x000D_ oranlarının yüksek basınçtaki davranışları incelenmiştir. Bazı malzemelerde, örneğin BC ve BO_x000D_ malzemelerinde, bor oranının artmasıyla iki boyutlu yapıdan üç boyutlu yapıya geçiş_x000D_ gözlemlenmiştir. Ayrıca yüksek bor oranlarında, B12 icosahedralların oluştuğu bulunmuştur. B12_x000D_ molekülüne ek olarak nano boyutunda B7, B10, B14, B16 kafes moleküllerinin oluşumu bazı_x000D_ malzemelerde gözlemlenmiştir. Modellenen malzemelerin her birinin yarıiletken özelliği gösterdiği_x000D_ fakat yasak band aralığında bor oranına bağlı genel bir eğilim olmayıp dalgalanmaların olduğu_x000D_ bulunmuştur. B12 moleküllerinin oluşumunun malzemelerin mekanik özelliğini dikkate değer bir_x000D_ şekilde etkilediği ve bor oranı yüksek olan malzemelerin daha sert bir özellik gösterdiği_x000D_ bulunmuştur. Yüksek basınç uygulamasıyla, malzemelerin daha yoğun bir amorf yapıya faz_x000D_ geçişişi yaptığı ve malzemeye bağlı olarak, faz geçişlerinin tersinir ya da tersinir olmayan faz_x000D_ geçişleri olduğu gözlemlenmiştir.

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